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Metaheuristic Analysis for Optimum Scheduling in FMS

Metaheuristic Analysis for Optimum Scheduling in FMSvon P. Sreenivas Sie sparen 19% des UVP sparen 19%
Über Metaheuristic Analysis for Optimum Scheduling in FMS

The survey work is carried out on simultaneous scheduling optimization with Machines and AGV¿s. The third chapter highlights various concepts of simultaneous scheduling. The significance of the scheduling in FMS environment is also considered and chapter four discusses the proposed Differential Evolution, Simulated Annealing, and a Tabu search, for the optimization of the simultaneous scheduling of AGV¿s and Machines. Fifth chapter depicts the various simultaneous scheduling Model Buildings with various configurations and discusses the proposed Differential Evolution, Simulated Annealing, and a Tabu search procedures followed in optimizing the simultaneous scheduling of AGV¿s and Machines and sixth chapter explains the procedure of Differential Evolution, Simulated Annealing, and a Tabu search provides comparison of proposed algorithm with the obtained results and the various observations of the performances of Meta-heuristic methods are enumerated. The final chapter seven gives the conclusion of the research work carried out on simultaneous scheduling of AGV¿s and Machine, and also discusses the scope for future work.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9786206790211
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 140
  • Veröffentlicht:
  • 16. Oktober 2023
  • Abmessungen:
  • 150x9x220 mm.
  • Gewicht:
  • 227 g.
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Beschreibung von Metaheuristic Analysis for Optimum Scheduling in FMS

The survey work is carried out on simultaneous scheduling optimization with Machines and AGV¿s. The third chapter highlights various concepts of simultaneous scheduling. The significance of the scheduling in FMS environment is also considered and chapter four discusses the proposed Differential Evolution, Simulated Annealing, and a Tabu search, for the optimization of the simultaneous scheduling of AGV¿s and Machines. Fifth chapter depicts the various simultaneous scheduling Model Buildings with various configurations and discusses the proposed Differential Evolution, Simulated Annealing, and a Tabu search procedures followed in optimizing the simultaneous scheduling of AGV¿s and Machines and sixth chapter explains the procedure of Differential Evolution, Simulated Annealing, and a Tabu search provides comparison of proposed algorithm with the obtained results and the various observations of the performances of Meta-heuristic methods are enumerated. The final chapter seven gives the conclusion of the research work carried out on simultaneous scheduling of AGV¿s and Machine, and also discusses the scope for future work.

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